Formation Damage Caused by Improper Mn3O4-Based Filter-Cake-Cleanup Treatments
Bibliographic record
Abstract
Summary Cleanup of filter cake is a difficult task and becomes more challenging when dealing with weighting materials [e.g., manganese tetraoxide (Mn3O4)]. Mn3O4 is a strong oxidizing agent and can be used as a catalyst because of its active phase, a nonstoichiometric Mn3O4 composed of an octahedral Mn2O3 phase and a tetrahedral MnO phase, which will result in complex interactions with most cleaning fluids. The reaction of selected organic acids and chelating agents with Mn3O4 particles as a function of time and temperature was studied. Solubility and compatibility tests of Mn3O4 particles with cleaning fluids were conducted using a high-pressure/hightemperature (HP/HT) see-through cell. Reaction kinetic tests were conducted using a three-neck round-bottom flask. Atomic absorption was used to measure manganese concentration, and X-ray diffraction was used to analyze solids remaining after the reaction. A white precipitate of manganese citrate was produced following the reaction of citric acid with Mn3O4 up to 284°F. The amount of precipitate was increased with temperature and initial acid concentration. An amino polycarboxylic acid chelating agent derived from L-glutamic acid (GLDA) (a chelant) reacted with Mn3O4 particles completely at 190°F. However, a large amount of a white was precipitate produced. Similarly, a white precipitate was observed with oxalic and tartaric acids. The reaction of diethylene triamine pentaacetic acide (DTPA) (a chelate) with Mn3O4 particles in a glass reactor produced Mn (silicates) at 212 and 284°F. The results of the present study will help drilling/completion engineers avoid using such cleaning fluids to prevent formation damage after filter-cake-removal treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".